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Retrieval-Augmented Generation (RAG) has been an effective approach to mitigate hallucinations in large language models (LLMs) by incorporating up-to-date and domain-specific knowledge.
Ms marco: A human generated machine reading comprehension dataset
Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, et al · 2016
Earlier work this paper cites.
Membership inference attacks against machine learning models. In 2017 IEEE symposium on security and privacy (SP) . IEEE, 3–18
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov. 2017 · 2017
Earlier work this paper cites.
Privacy risk in machine learning: Analyzing the connection to overfitting. In 2018 IEEE 31st computer security foundations symposium (CSF) . IEEE, 268–282
Samuel Yeom, Irene Giacomelli, Matt Fredrikson, and Somesh Jha. 2018 · 2018
Earlier work this paper cites.
Generalization through memorization: Nearest neighbor language models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom B Brown. 2020 · 2020
Earlier work this paper cites.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
Earlier work this paper cites.
Extracting training data from large language models. In 30th USENIX Security Symposium (USENIX Security 21) . 2633–2650
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al · 2021
Earlier work this paper cites.
Sentence-t5: Scalable sentence encoders from pre-trained text-to-text models
Jianmo Ni, Gustavo Hernandez Abrego, Noah Constant, Ji Ma, Keith B Hall, Daniel Cer, and Yinfei Yang. 2021 · 2021
Earlier work this paper cites.
Automatic generation of cloze items for repeated testing to improve reading comprehension
Albert CM Yang, Irene YL Chen, Brendan Flanagan, and Hiroaki Ogata. 2021 · 2021
Earlier work this paper cites.
Precise zero-shot dense retrieval without relevance labels
Luyu Gao, Xueguang Ma, Jimmy Lin, and Jamie Callan. 2022 · 2022
Earlier work this paper cites.
Membership inference attacks on machine learning: A survey
Hongsheng Hu, Zoran Salcic, Lichao Sun, Gillian Dobbie, Philip S Yu, and Xuyun Zhang. 2022 · 2022
Earlier work this paper cites.
Few-shot learning with retrieval augmented language models
Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave. 2022 · 2022
Earlier work this paper cites.
Lawsuit takes aim at the way A.I. is built
Cade Metz. 2022 · 2022
Earlier work this paper cites.
Uprise: Universal prompt retrieval for improving zero-shot evaluation
Daixuan Cheng, Shaohan Huang, Junyu Bi, Yuefeng Zhan, Jianfeng Liu, Yujing Wang, Hao Sun, Furu Wei, Denvy Deng, and Qi Zhang. 2023 · 2023
Earlier work this paper cites.
Case 3:23-cv-03416
Ryan J. Clarkson, Yana Hart, Tiara Avaness, and Valter Malkhasyan. 2023 · 2023
Earlier work this paper cites.
Retrieval-augmented generation for large language models: A survey
Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, and Haofen Wang. 2023 · 2023
Cited alongside, same era.
Foundation models and fair use
Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A Lemley, and Percy Liang. 2023 · 2023
Cited alongside, same era.
Baseline defenses for adversarial attacks against aligned language models
Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, and Tom Goldstein. 2023 · 2023
Cited alongside, same era.
Active retrieval augmented generation
Zhengbao Jiang, Frank F Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, and Graham Neubig. 2023 · 2023
Cited alongside, same era.
C-Pack: Packaged Resources To Advance General Chinese Embedding
Shitao Xiao, Zheng Liu, Peitian Zhang, and Niklas Muennighoff. 2023 · 2023
Later among the works it cites.
Augmentation-adapted retriever improves generalization of language models as generic plug-in
Zichun Yu, Chenyan Xiong, Shi Yu, and Zhiyuan Liu. 2023 · 2023
Later among the works it cites.
Siren’s song in the AI ocean: a survey on hallucination in large language models
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, et al · 2023
Later among the works it cites.
Maya Anderson, Guy Amit, and Abigail Goldsteen. 2024 · 2024
Closest in time.
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Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, and Colin Raffel. 2023 · 2023
Cited alongside, same era.
Knowledge graph-augmented language models for knowledge-grounded dialogue generation
Minki Kang, Jin Myung Kwak, Jinheon Baek, and Sung Ju Hwang. 2023 · 2023
Cited alongside, same era.
Query rewriting for retrieval-augmented large language models
Xinbei Ma, Yeyun Gong, Pengcheng He, Hai Zhao, and Nan Duan. 2023 · 2023
Cited alongside, same era.
Mask and cloze: automatic open cloze question generation using a masked language model
Shoya Matsumori, Kohei Okuoka, Ryoichi Shibata, Minami Inoue, Yosuke Fukuchi, and Michita Imai. 2023 · 2023
Cited alongside, same era.
Membership inference attacks against language models via neighbourhood comparison
Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, and Taylor Berg-Kirkpatrick. 2023 · 2023
Cited alongside, same era.
Silo language models: Isolating legal risk in a nonparametric datastore
Sewon Min, Suchin Gururangan, Eric Wallace, Weijia Shi, Hannaneh Hajishirzi, Noah A Smith, and Luke Zettlemoyer. 2023 · 2023
Cited alongside, same era.
In-context retrieval-augmented language models
Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, and Yoav Shoham. 2023 · 2023
Cited alongside, same era.
Detecting pretraining data from large language models
Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, and Luke Zettlemoyer. 2023 · 2023
Cited alongside, same era.
Matthijs Douze, Alexandr Guzhva, Chengqi Deng, Jeff Johnson, Gergely Szilvasy, Pierre-Emmanuel Mazaré, Maria Lomeli, Lucas Hosseini, and Hervé Jégou. 2024 · 2024
Closest in time.
Do membership inference attacks work on large language models?
Michael Duan, Anshuman Suri, Niloofar Mireshghallah, Sewon Min, Weijia Shi, Luke Zettlemoyer, Yulia Tsvetkov, Yejin Choi, David Evans, and Hannaneh Hajishirzi. 2024 · 2024
Closest in time.
From local to global: A graph rag approach to query-focused summarization
Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, and Jonathan Larson. 2024 · 2024
Closest in time.
Seeing Is Believing: Black-Box Membership Inference Attacks Against Retrieval Augmented Generation
Yuying Li, Gaoyang Liu, Yang Yang, and Chen Wang. 2024 · 2024
Closest in time.
Zhenting Qi, Hanlin Zhang, Eric Xing, Sham Kakade, and Himabindu Lakkaraju. 2024 · 2024
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Certifiably Robust RAG against Retrieval Corruption
Chong Xiang, Tong Wu, Zexuan Zhong, David Wagner, Danqi Chen, and Prateek Mittal. 2024 · 2024
Closest in time.
The good and the bad: Exploring privacy issues in retrieval-augmented generation (rag)
Shenglai Zeng, Jiankun Zhang, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, et al · 2024
Closest in time.
The good and the bad: Exploring privacy issues in retrieval-augmented generation (rag)
Shenglai Zeng, Jiankun Zhang, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, et al · 2024
Closest in time.
Right to be forgotten in the era of large language models: Implications, challenges, and solutions
Dawen Zhang, Pamela Finckenberg-Broman, Thong Hoang, Shidong Pan, Zhenchang Xing, Mark Staples, and Xiwei Xu. 2024 · 2024
Closest in time.
Trustworthiness in Retrieval-Augmented Generation Systems: A Survey
Yujia Zhou, Yan Liu, Xiaoxi Li, Jiajie Jin, Hongjin Qian, Zheng Liu, Chaozhuo Li, Zhicheng Dou, Tsung-Yi Ho, and Philip S Yu. 2024 · 2024
Closest in time.
Poisonedrag: Knowledge poisoning attacks to retrieval-augmented generation of large language models
Wei Zou, Runpeng Geng, Binghui Wang, and Jinyuan Jia. 2024 · 2024
Closest in time.